single.snp.tests {snpMatrix} | R Documentation |
This function carries out tests for association between phenotype and a series of single nucleotide polymorphisms (SNPs), within strata defined by a possibly confounding factor. SNPs are considered one at a time and both 1-df and 2-df tests are calculated. For a binary phenotype, the 1-df test is the Cochran-Armitage test (or, when stratified, the Mantel-extension test).
single.snp.tests(phenotype, stratum, data = sys.parent(), snp.data, subset, snp.subset)
phenotype |
A vector containing the values of the phenotype |
stratum |
Optionally, a factor defining strata for the analysis |
data |
A dataframe containing the phenotype and
stratum data. The row names of this are linked with the row
names of the snps argument to establish correspondence of
phenotype and genotype data. If this argument is not supplied,
phenotype and stratum are evaluated in the calling
environment and should be in the same order as rows of snps |
snp.data |
An object of class "snp.matrix" containing the SNP
genotypes to be tested |
subset |
A vector or expression describing the subset of subjects
to be used in teh analysis. This is evaluated in the same
environment as the phenotype and stratum arguments |
snp.subset |
A vector describing the subset of SNPs to be considered. Default action is to test all SNPs. |
Formally, the test statistics are score tests for generalized linear models with canonical link. That is, they are inner products between genotype indicators and the deviations of phenotypes from their stratum means. Variances (and covariances) are those of the permutation distribution obtained by randomly permuting phenotype within stratum.
The subset
argument can either be a logical vector of length
equal to the length of the vector of phenotypes, an integer vector
specifying positions in the data
frame, or a character vector
containing names of the selected rows in the data
frame. Similarly, the snp.subset
argument can be a logical,
integer, or character vector.
A dataframe, with columns
chi2.1df |
Cochran-Armitage type test for additive genetic component |
chi2.2df |
Chi-squared test for both additive and dominance components |
N |
The number of valid data points used |
The behaviour of this function for objects of class
X.snp.matrix
is as described by Clayton (2008). Males are
treated as homozygous females and corrected variance estimates are
used.
David Clayton david.clayton@cimr.cam.ac.uk
Clayton (2008) Testing for association on the X chromosome Biostatistics (In press)
data(testdata) results <- single.snp.tests(cc, stratum=region, data=subject.data, snp.data=Autosomes, snp.subset=1:10) summary(results) # QQ plot - see this-is-escaped-codenormal-bracket52bracket-normal qq.chisq(results$chi2.1df) qq.chisq(results$chi2.2df)